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false-positive

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Safety regions research is a well-known task for ML and the main focus is to avoid false positives, i.e., including in the safe region unsafe points. In this repository, two methods for the research of zero FPR regions are proposed: the first one is based simply on the reduction of the SVDD radius until only safe points are enclosed in the SVDD …

  • Updated Nov 21, 2022
  • MATLAB

Machine learning for credit card default. Precision-recalls are calculated due to imbalanced data. Confusion matrices and test statistics are compared with each other based on Logit over and under-sampling methods, decision tree, SVM, ensemble learning using Random Forest, Ada Boost and Gradient Boosting. Easy Ensemble AdaBoost classifier appear…

  • Updated Jul 24, 2020
  • Jupyter Notebook

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